تحقیقات آب و خاک ایران

تحقیقات آب و خاک ایران

تاثیر عدم قطعیت هدایت هیدرولیکی و تعداد نمونه در روش مونت کارلو بر تغییرات زمانی تحکیم خاک

نوع مقاله : مقاله پژوهشی

نویسندگان
1 عضو هیات علمی گروه مهندسی آب دانشگاه گیلان
2 دانشجوی دانشگاه گیلان
چکیده
نقش عدم­قطعیت هدایت هیدرولیکی به عنوان عاملی مؤثر در تحلیل احتمالاتی تحکیم خاک حائز اهمیت می­باشد. در تحقیق حاضر، برنامه­ای رایانه­ای در محیط MATLAB توسعه داده شد و پس از حل عددی معادله دیفرانسیل تحکیم به روش تفاضل محدود، از آن به عنوان راه­حل پایه، در شبیه­سازی مونت­کارلو استفاده گردید. همچنین تأثیر تعداد نمونه تصادفی در مدل احتمالاتی تحکیم به روش مونت­کارلو با کاربرد 100 و 1000 نمونه از توزیع­ لوگ-نرمال هدایت هیدرولیکی مربوط به زمینی در سراوان گیلان بررسی شد. نتایج نشان داد که با افزایش زمان، منحنی توزیع احتمالاتی فشار آب منفذی هموارتر و عدم­قطعیت بیش­تر می­گردد. افزایش تعداد نمونه هدایت هیدرولیکی از 100 نقطه به 1000 نقطه، تأثیر کمی بر توزیع احتمالاتی فشار آب منفذی نشان داد. همچنین بیش­ترین ضریب نیکویی برازش توزیع نرمال بر فشار آب منفذی در نزدیک به سطح خاک و 23 درصد بیش از مرکز لایه خاک به دست آمد.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

Effect of uncertainty of hydraulic conductivity and number of samples in Monte-Carlo method on time-dependent variation of soil consolidation

نویسندگان English

Amir Malekpour 1
Nima Sadeghiyan 2
Mahtab Mohammadi 2
1 Academic staff, Dept. Water Engineering, University of Guilan
2 B.Sc. Student of University of Guilan
چکیده English

The uncertainty of hydraulic conductivity plays an important role in probabilistic analysis of consolidation of soils. In current research, a computer program was developed in MATLAB and solving the governing partial differential equation using numerical finite difference method, it was applied as the basis solution to Monte-Carlo simulation. Meanwhile, the effect of number of random samples was investigated applying 100 and 1000 samples from log-normal distribution of hydraulic conductivity (related to a land located in Saravan-Guilan) into the probabilistic consolidation model. The results showed that the probabilistic distribution curve of pore-water pressure becomes flatter with time and the uncertainty increases. Increasing the number of hydraulic conductivity samples from 100 to 1000 caused negligible effect on the probabilistic distribution of pore-water pressure. Moreover, the greatest goodness of fit of normal distribution to pore-water pressure obtained close to the soil surface and 23 percent greater than the center of soil layer.

کلیدواژه‌ها English

Fine-grained soil
Log-normal distribution
pore-water pressure
probabilistic analysis
Alizadeh, A., (2014). Principles of applied hydrology. Mashhad Ferdowsi Univ. Press(In Farsi).
Baecher, G. B. and Christian, J. T. (2003). Reliability and statistics in geotechnical engineering, John Wiley & Son, West Sussex England.
Bari, M.W., Shahin. M.A. and Nikraz, H.R. (2013). Probabilistic analysis of soil consolidation via prefabricated vertical drains. International Journal of Geomechanics. 13(6):877-81.
Chang, C.S. (1985). Uncertainty of One-Dimensional consolidation analysis. J. Geotech. Geoenviron. Eng. 111(12):1411-24.
Cheng, Y., Zhang, L.L., Li, J.H., Zhang, L.M., Wang, J.H. and Wang, D.Y. (2017). Consolidation in spatially random unsaturated soils based on coupled flow-deformation simulation.International Journal for Numerical and Analytical Methods in Geomechanics 41(5):682-706.
Di-Agostino, R.B. and Massaro, J.M. (2013). Goodness of fit tests. Handbook of logistic distribution. ISBN: 0-8247-8587-8.
Fenton, G.A. and Griffiths, D.V. (2002). Probabilistic foundation settlement on spatially random soil. J. Geotech. Geoenviron. Eng. 128 (5):381-390.
Gilbert, R.B. (2015). Important role of uncertainty in forensic geotechnical engineering. Series of Development in Geotechnical Engineering, Springer, 493-503.
Griffiths, D.V and Fenton, G.A. (2009). Probabilistic   settlement analysis by stochastic and random finite-element methods. J. Geotech. Geoenviron. Eng. 135(11):1629-1637.
Gui, S., Zhang, R., Turner, J.P. and Xue, X. (2000). Probabilistic slope stability analysis with stochastic soil hydraulic conductivity. J. Geotech. Geoenviron. Eng. 126(1):1-9.
Hoeksema, R. J. and Kitanidis, P. K. (1985). Analysis of the spatial structure of properties of selected aquifers. Water Resource Research 21(4): 563-572.
Houmadi, Y., Ahmed, A. and Soubra, A. H. (2012). Probabilistic analysis of a one-dimensional soil consolidation problem. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards. 6(1):36-49.
Huang, J. and Griffiths, D.V. (2009). Probabilistic analysis of coupled soil consolidation. J. Geotech. Geoenviron. Eng. 136(3):417-430.
Lumb, P. (1966). The variability of natural soils.  Canadian Geotech. J. 3(2): 74-97.
Nadim, F. (2015). Accounting for uncertainty and variability in geotechnical characterization of offshore sites. Geotechnical safety and risk, IOS Press. doi: 10.3233/978-1-61499-580-7-23.
Pohl, C. (2011). Determination of characteristic soil values by statistical methods. ISGR Geotechnical Safety and Risk 427-434.
Pyrah, I. C. (1996). One -dimensional consolidation of layered soils. Geotechnique. 46(3): 555-560.
Ronold, K.O. (1989). Probabilistic consolidation analysis with model updating. Journal of Geotechnical Engineering 115(2):199-210.
Sebai, S. and Belkacemi, S. (2016). Consolidation coefficient by combined probabilistic and least residuals methods. Geotechnical Testing Journal 39(5): 891-897.
Wang, Y., Zhao, T. and Cao, Z. (2015). Site-specific probability distribution of geotechnical Properties. Computers and Geotechnics 70: 159-168.
Zhai, H. and Benson, C.H. (2006). The log-normal distribution for hydraulic conductivity of compacted clays : two or three parameters ?. Geotech. Geoenviron. Eng. 24(5):1149-1162.
Zomorodian, M. and Zerang-Sani, F. (2015). Investigation of the effect of soil mechanic parameters on bearing capacity of strip footings. Sharif Civil Eng. J. 31(1-1): 129-136 (In Farsi)